Regional optical networks combine long reach with complicated mesh designs and a variety of fiber types, such as Non-dispersion Shifted Fiber (NDSF), Lambda Shifted (LS), Truewave (TW), Truewave Classic (TWC), Truewave Reduced Slope (TWRS), Large Effective Area Fiber (LEAF), Enhanced LEAF (eLEAF), Dispersion Shifted Fiber (DSF), Teralight, and the like. Traffic demands can have variable lengths and can overlap along portions of the network. Optimizing network performance while minimizing network cost under these circumstances in meshed designs is a challenge.
Most equipment manufacturers have computer tools to assist the network designer in the process of choosing and configuring telecommunication equipment. In the simplest designs, equipment configuration is preset and the tool attempts to place the equipment to create the most efficient network. More sophisticated tools both choose the equipment and recommend the most appropriate parameter settings (hardware and/or software) in order to achieve the desired network cost points and performance. For example, these tools can provide amplifier and regenerator locations based upon an input of traffic demands A-Z, sites, and network parameters (e.g., fiber type, site distances, etc.).
Choosing the optimal launch powers for demands on a network has a direct bearing on the efficiency and cost to build and maintain that network. If launch power is not optimized, individual traffic demands are more likely to require regeneration. Regeneration increases initial network equipment cost at deployment, since at a minimum more transceivers and more filters are required. More equipment is also likely to increase lifetime operating cost. Thus choosing the optimal launch power decreases equipment count and cost. In addition, consider the impact of launch power optimization on demands which do not require regeneration, even with non-optimized launch power. These demands will have less operating margin than demands with optimized launch power. Increased operating margin is reasonably expected to lead to improved traffic performance and greater network reliability over the equipment lifetime.
Finding the optimal launch power for any given demand on a network is a balancing act between optical signal-to-noise ratio (OSNR) and nonlinear penalties, such as Four Wave Mixing (FWM), Self Phase Modulation (SPM), Cross Phase Modulation (XPM), and the like. If the launch power is too low, the OSNR is insufficient for a good signal; launching a traffic demand with higher power increases the OSNR at the receiver. However, increasing signal launch power increases the nonlinear penalties. If the launch power is too high, the nonlinear penalties are excessive and performance suffers. To further complicate matters, nonlinear penalties are a function not only of launch power and fiber type, but also of span and link characteristics (i.e., dispersion, number of spans, individual span length, and the like).
In a simple linear, point-to-point network without overlapping lightpaths, it is fairly straightforward to calculate the optimum launch power for best receiver performance. In linear networks with partially overlapping lightpaths, the optimal launch power for each of the demands can be computed independently. The designer is then likely to discover that the optimal launch powers on some spans and links may be different for different demands. If the network is not too large and the number of overlapping demands is not too high, the network designer may be able to find launch powers that satisfy all demands.
In meshed networks, the problem continues to grow more complex with the increasing possibilities for partially overlapping demands with otherwise diverse routing. Some equipment providers solve the problem by simply choosing a default span launch power which may be allowed to vary by fiber type, but is otherwise constant through the network. This power is generally chosen to be low enough so that the nonlinear penalties of the longest guaranteed demands remain below a maximum, pre-determined threshold.
There are a number of problems with this solution, since this approach is not at all customized to the nature of the particular network in question. For example, if the network has few (or no) long demands, nonlinear penalties are minimal and this approach forces the launch power to be artificially low. Better performance might be achieved with higher powers, particularly if the network has a significant number of high loss spans. Conversely, if the network has many long demands and typical spans are relatively short and low loss, better network performance is likely to be achieved with relatively low launch powers that avoid triggering nonlinear penalties.
A brute force method to optimize network launch power by trying out all possible launch power permutations is theoretically possible, but is not a reasonable solution for all but the smallest, simplest networks.